Fuquay Varina – The National Institute of General Medical Sciences (NIGMS) recently awarded $149,999 to Collaborations Pharmaceuticals, Inc. (CPI) to develop software that could make public data more amenable to those scientists who want to use it to build computational models to help their research.

There are massive publically accessible databases that include a broad variety of disease targets and absorption, distribution, metabolism, excretion and toxicology (ADMET) properties that are not in a form that is immediately ready for machine learning model building or accessible for use by small research and development (R&D) organizations that do not have their own in-house cheminformatics teams. This project will compile a comprehensive collection of these datasets (e.g. databases like PubChem, ChEMBL etc) for structure-activity data. This will enable the user to quickly and automatically use machine learning models for various targets and properties that could be of value for drug discovery.

“Being able to use transparent computational models simultaneously for visualizing activity trends for multiple targets (both diseases and ADMET) removes the burden of curation or purchasing and maintaining expensive software, and drastically simplifies the addition of new data. It also represents a new frontier of drug discovery as a world of small, agile distributed R&D organizations has access to valuable public datasets that can inform their research. Such computational models will assist in drug repurposing efforts internally and with our collaborators while likely identifying new compounds for a wide array of drug discovery projects” said Sean Ekins, CEO CPI.

“We are very grateful to NIGMS for funding so we can illustrate how computational approaches can be used to repurpose drugs already approved for other uses and instead use for neglected and rare diseases” said Dr. Ekins.

About Collaborations Pharmaceuticals, Inc.

Collaborations Pharmaceuticals, Inc. performs research and development on innovative therapeutics for multiple rare and infectious diseases. We partner with leading academics, companies and foundations to identify and translate early preclinical to clinical stage assets. We have considerable experience in preclinical and computational approaches to drug discovery and toxicity prediction. For more information, please visit http://www.collaborationspharma.com/